5833 20220928100756.0 CTALK-2022-0077 De Plaen, R. Extracting Microseismic Ground Motion From Legacy Seismograms 2022 2022-09-05 Before digital recordings became available in the 1970s, the ground motion was recorded using ink on white paper, scratching black-smoked paper, or light on photographic paper. While those analog seismic records offer unique continuous observations from the last century, most of them are now stacked and archived in boxes and potentially exposed to physical decay and permanent loss. To preserve those records and ultimately subject them to modern methods of analysis, it is time-sensitive to scan and digitize them. Here, we worked on a method for automatic digitization of paper seismograms using image processing and machine learning to extract microseismic ground-motion periods and amplitudes. We implemented the method on legacy data recorded at the Royal Observatory of Belgium to extract power spectral densities for major storms during the last century, which are compared with modeled microseisms levels computed using a numerical ocean wave model. This further shows how digitizing analog seismograms does not only preserve the scientific legacy but also makes new research possible by bringing analog data to the digital age. FSIRI/ 33/ EP1 NO analog seismograms seismic noise oceanic storms digitalization machine learning oceanic climate Lecocq, T. Lemenkova, P. Debeir, O. Ardhuin, F. De Carlo, M. 3rd European Conference on Earthquake Engineering & Seismology. Bucharest, Romania martin.zeckra@observatory.be 1765871 http://publi2-as.oma.be/record/5833/files/2022_3ECEES_DePlaen.pdf 11535 http://publi2-as.oma.be/record/5833/files/2022_3ECEES_DePlaen.jpg?subformat=icon-180 icon-180 9694 http://publi2-as.oma.be/record/5833/files/2022_3ECEES_DePlaen.gif?subformat=icon icon Contributed CTALKCONT